AI industry trends in 2023

Artificial Intelligence (AI) often makes headlines with its latest advancements and applications – from art generators like DALL.E-2 to the infamous human-like content generator ChatGPT. In fact, you’ll likely find demand is now so high that it’s at capacity.

This popularity has once again raised questions about the future of AI, especially the opportunities and risks for it in business. Are we training ethically and without bias? Is it ready to replace some of the more admin-heavy and time-consuming parts of day-to-day life and work? What happens when it’s smart enough to rewrite its own code? How will it impact privacy and security?

Whatever your stance, these technological advancements present increasingly exciting possibilities to scale human intellect. To realise this vision, investment is needed and the industry has it. Now in its second year, the UK government’s National AI Strategy aims to boost business use of AI, attract international investment, and develop the next generation of tech talent. That investment was at $3.6 billion last year alone to be precise. Despite the economic downturn, it has become one of the fastest-growing UK tech sectors.

So as AI technology embeds itself in our lives and work, what trends can we expect to see for 2023?

Five AI trends to watch

Generative AI

Starting 2023 on a popular note thanks to ChatGPT and DALL.E-2, generative AI models produce content rather than analysing or acting on existing data. This opens up a world of text, audio, and visual possibilities such as automating blogging and artwork creation or programming code. Essentially, this steps away from automating routine and repetitive tasks, and focuses on creative outputs to produce original digital content and enhance human intellect.

Adaptive AI

Once an AI is trained, the opportunities don’t stop there. Continuously retraining models to ensure they learn and adapt based on new experiences is important to keep pace with user expectations. Adaptive AI allows for adjustments around real-world changes and new data that wasn’t foreseen or available when the original code was written. For businesses, this means greater resilience and the flexibility to adapt technology quickly to meet the demands of the day.

Ethical AI

As AI mimics human intelligence, ethics rightly come into question. To build trust, fundamental values must be taken into account when training AI models, ranging from individual rights to non-discrimination. The industry is committed to addressing this, and we can expect an increasing focus on representative and diverse sources to train AI that avoids prejudice in automated outcomes. In fact, the UK Government recently launched a committee to explore regulating it. Whilst leaders in the AI space, such as IBM, have outlined three ethical principles that guide their Artificial Intelligence work.

Low-code/no-code AI

AI is rooted in developers, technicians, and engineers feeding the technology complex datasets. But the rise of plug-and-play options has made AI more accessible to the masses. Low-code opens the doors to more tech professionals, while no-code enables those with zero coding knowledge to embrace AI through drag-and-drop interfaces. This means digital assets can be quickly created using prebuilt components, allowing business users to act quickly to bridge the gap of unmet software needs. Companies such as Viso Suite’s computer vision and deep learning applications, and Airtable’s software democratisation tools are great examples.

Sustainable AI

Most businesses are required to have long-term emission reduction targets in line with the 2050 net zero goal. AI has many applications in driving sustainability initiatives from reducing its own environmental footprint, by shifting to greener and renewable sources, to identifying changes in satellite images for tackling deforestation and poaching. Whilst companies such as Terraview’s crop management platform for the wine industry use AI for climate and crop management via machine intelligence to improve yields, optimise water usage, and account for seasonality.

Building trust and awareness for your business

All this innovation, however, may never reach businesses and consumers if the AI never moves out of the research and development (R&D) stage. While investment is booming, a harsh economic climate means those companies must now deliver profit, not just innovation. This means becoming commercially viable. One key strand of this is the right marketing strategy, which includes:

Brand messaging

Communicating the benefits and USPs of highly technical applications isn’t straightforward, so spending time on your brand positioning is integral. Find a PR partner that will immerse themselves in your business and do their due diligence when preparing your comms strategy

Brand awareness

From reaching customers to attracting investors, raising your business’s brand awareness has many benefits. Not only will this strategy position you as a credible player in the crowded space, but you’ll build the foundations to shout about your achievements and unique case studies

Web and social presence

A holistic approach to your comms strategy is needed, especially when considering both your stakeholders and your business’s profile. Whether that’s consistency in your branding and messaging across both your website and socials, or building unique content to share with your audience

To find out more about how The PHA Group can help your Artificial Intelligence business create or enhance its PR strategy, speak to a Technology PR expert today.

Get in touch with the team